对于可转移的局部密度潜力的温度依赖的长度尺度.
1Department of Chemistry, Penn State University, University Park, Pennsylvania 16802, USA.
The Journal of chemical physics
|August 17, 2023
概括
本研究探讨了粗粒度 (CG) 模型中温度依赖的局部密度 (LD) 潜力. 优化的LD潜能准确地预测了不同温度的分子液体行为,简化了模拟.
科学领域:
- 计算化学是一种计算化学.
- 材料科学是一种材料科学.
- 统计力学就是统计力学.
背景情况:
- 粗粒度 (CG) 模型对于模拟大型分子系统至关重要.
- 传统的CG模型经常使用对潜力,但局部密度 (LD) 潜力提供了更好的准确性.
- 了解LD电位的温度依赖性对于它们更广泛的应用至关重要.
研究的目的:
- 在多尺度粗粒度 (MS-CG) 模型中研究局部密度 (LD) 潜力的温度依赖性.
- 为分子液体开发精确和可转移的CG电位.
- 建立一种方法,在没有广泛的模拟的情况下,预测新状态点的潜力.
主要方法:
- 采用了多尺度粗粒度 (MS-CG) 力匹配变化原理.
- 在环境压力下的分子液体的单位CG模型中,参数化的对和LD潜力.
- 分析了LD潜在精度对局部密度长度尺度 (rc) 的灵敏度.
主要成果:
- MS-CG LD 潜力的准确性取决于所选择的长度尺度 (rc).
- 一个最佳的长度尺度 (rc*) 允许MS-CG潜能准确地描述参考状态点和跨温度的转移.
- 在环境压力下,最佳的LD长度尺度与温度线性变化.
- 一个取决于温度的LD长度尺度使MS-CG LD潜力不受温度的影响,而对潜力则线性变化.
- 预测的潜力有时会超过针对特定状态点优化的潜力.
结论:
- 取决于温度的最佳长度尺度简化了分子液体的MS-CG电位的参数化.
- 这种方法可以准确地预测新状态点的潜力,减少了对额外原子模拟的需求.
- 这些发现为模拟不同温度的分子液体提供了一个计算效率高的策略.
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